# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve. # #Licensed under the Apache License, Version 2.0 (the "License"); #you may not use this file except in compliance with the License. #You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # #Unless required by applicable law or agreed to in writing, software #distributed under the License is distributed on an "AS IS" BASIS, #WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. #See the License for the specific language governing permissions and #limitations under the License. from __future__ import absolute_import from __future__ import division from __future__ import print_function import distutils.util import six import paddle.fluid as fluid def print_arguments(args): """Print argparse's arguments. Usage: .. code-block:: python parser = argparse.ArgumentParser() parser.add_argument("name", default="Jonh", type=str, help="User name.") args = parser.parse_args() print_arguments(args) :param args: Input argparse.Namespace for printing. :type args: argparse.Namespace """ print("----------- Configuration Arguments -----------") for arg, value in sorted(six.iteritems(vars(args))): print("%s: %s" % (arg, value)) print("------------------------------------------------") def add_arguments(argname, type, default, help, argparser, **kwargs): """Add argparse's argument. Usage: .. code-block:: python parser = argparse.ArgumentParser() add_argument("name", str, "Jonh", "User name.", parser) args = parser.parse_args() """ type = distutils.util.strtobool if type == bool else type argparser.add_argument( "--" + argname, default=default, type=type, help=help + ' Default: %(default)s.', **kwargs) def check_gpu(use_gpu): """ Log error and exit when set use_gpu=true in paddlepaddle cpu version. """ err = "Config use_gpu cannot be set as true while you are " \ "using paddlepaddle cpu version ! \nPlease try: \n" \ "\t1. Install paddlepaddle-gpu to run model on GPU \n" \ "\t2. Set use_gpu as false in config file to run " \ "model on CPU" try: if use_gpu and not fluid.is_compiled_with_cuda(): logger.error(err) sys.exit(1) except Exception as e: pass def get_device_count(): try: device_num = max(fluid.core.get_cuda_device_count(), 1) except: device_num = 1 return device_num